Gradual Distributed Real-Coded Genetic Algorithms
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IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Materia
Crossover operator Distributed genetic algorithms Multiresolution Premature convergence Selective pressure
Date
2000Referencia bibliográfica
F. Herrera and M. Lozano, "Gradual distributed real-coded genetic algorithms," in IEEE Transactions on Evolutionary Computation, vol. 4, no. 1, pp. 43-63, April 2000, [doi: 10.1109/4235.843494]
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CICYT TIC96-0778Abstract
A major problem in the use of genetic algorithms
is premature convergence, a premature stagnation of the search
caused by the lack of diversity in the population. One approach
for dealing with this problem is the distributed genetic algorithm
model. Its basic idea is to keep, in parallel, several subpopulations
that are processed by genetic algorithms, with each one being
independent of the others. Furthermore, a migration mechanism
produces a chromosome exchange between the subpopulations.
Making distinctions between the subpopulations by applying
genetic algorithms with different configurations, we obtain the
so-called heterogeneous distributed genetic algorithms. These
algorithms represent a promising way for introducing a correct
exploration/exploitation balance in order to avoid premature
convergence and reach approximate final solutions.
This paper presents the gradual distributed real-coded genetic
algorithms, a type of heterogeneous distributed real-coded genetic
algorithms that apply a different crossover operator to each subpopulation. The importance of this operator on the genetic algorithm’s performance allowed us to differentiate between the subpopulations in this fashion. Using crossover operators presented
for real-coded genetic algorithms, we implement three instances of
gradual distributed real-coded genetic algorithms. Experimental
results show that the proposals consistently outperform sequential
real-coded genetic algorithms and homogeneous distributed realcoded genetic algorithms, which are equivalent to them and other
mechanisms presented in the literature. These proposals offer two
important advantages at the same time: better reliability and accuracy.